Professors Ruth Baker and Antoine Jerusalem have had an article on mechanistic versus machine learning published in Biology Letters.
The full title for their opinion piece is: Mechanistic models versus machine learning, a fight worth fighting for the biological community? They contributed to the piece, along with two other authors, Jose-Maria Peña and Jayaratnam Jayamohan.
The abstract reads: “90% of the world’s data have been generated in the last five years. A small fraction of these data is collected with the aim of validating specific hypotheses. These studies are led by the development of mechanistic models focussed on the causality of input-output relationships. However, the vast majority is aimed at supporting machine learning models, in particular in the biomedical and clinical sciences. Recent successes now beg the question of whether mechanistic models are still relevant in this area. Said otherwise, why should we try to understand the mechanisms of disease progression when we can use machine learning tools to directly predict disease outcome?”
Congratulations to Professor Jerusalem and Professor Baker on the publication!
The article can be read here: http://rsbl.royalsocietypublishing.org/lookup/doi/10.1098/rsbl.2017.0660
